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Conditioning Information and Variance Bounds on Pricing Kernels with Higher-Order Moments: Theory and Evidence

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Author Info
Fousseni Chabi-Yo
Abstract

The author develops a strategy for utilizing higher moments and conditioning information efficiently, and hence improves on the variance bounds computed by Hansen and Jagannathan (1991, the HJ bound) and Gallant, Hansen, and Tauchen (1990, the GHT bound). The author's bound incorporates variance risk premia. It reaches the GHT bound when non-linearities in returns are not priced. The author also provides an optimally scaled bound with conditioning information, higher moments, and variance risk premia that improves on the Bekaert and Liu (2004, the BL bound) optimally scaled bound. This bound reaches the BL bound when nonlinearities in returns are not priced. When the conditional first four moments are misspecified, the author's optimally scaled bound remains a lower bound to the variance on pricing kernels, whereas the BL bound does not. The author empirically illustrates the behaviour of the bounds using Bekaert and Liu's (2004) econometric models. He also uses higher moments and conditioning information to provide distance measures that improve on the Hansen and Jagannathan distance measures. The author uses these distance measures to evaluate the performance of asset-pricing models. Some existing pricing kernels are able to describe returns ignoring the impact of higher moments and variance risk premia. When accounting for the impact of higher moments and variance risk premia, these same pricing kernels have difficulty in explaining returns on the assets and are unable to price non-linearities or higher moments.

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Paper provided by Bank of Canada in its series Working Papers with number 06-38.

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Length: 56 pages
Date of creation: 2006
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Handle: RePEc:bca:bocawp:06-38

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Related research
Keywords: Financial markets; Market structure and pricing;

Find related papers by JEL classification:
G12 - Financial Economics - - General Financial Markets - - - Asset Pricing
G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
C61 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Optimization Techniques; Programming Models; Dynamic Analysis

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    Other versions:
  2. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February. [Downloadable!] (restricted)
  3. Constantinides, George M & Duffie, Darrell, 1996. "Asset Pricing with Heterogeneous Consumers," Journal of Political Economy, University of Chicago Press, vol. 104(2), pages 219-40, April. [Downloadable!] (restricted)
    Other versions:
  4. Hansen, Lars Peter & Richard, Scott F, 1987. "The Role of Conditioning Information in Deducing Testable," Econometrica, Econometric Society, vol. 55(3), pages 587-613, May. [Downloadable!] (restricted)
  5. Bansal, Ravi & Viswanathan, S, 1993. " No Arbitrage and Arbitrage Pricing: A New Approach," Journal of Finance, American Finance Association, vol. 48(4), pages 1231-62, September. [Downloadable!] (restricted)
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  10. John Y. Campbell & John H. Cochrane, 2000. "Explaining the Poor Performance of Consumption-based Asset Pricing Models," Journal of Finance, American Finance Association, vol. 55(6), pages 2863-2878, December. [Downloadable!] (restricted)
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  12. Chapman, D.A., 1996. "Approximating the Asset Pricing Kernel," Papers 96-02, Rochester, Business - Financial Research and Policy Studies.
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  18. Geert Bekaert, 2004. "Conditioning Information and Variance Bounds on Pricing Kernels," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 17(2), pages 339-378. [Downloadable!] (restricted)
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  19. Tobias J. Moskowitz & Mark Grinblatt, 1999. "Do Industries Explain Momentum?," Journal of Finance, American Finance Association, vol. 54(4), pages 1249-1290, 08. [Downloadable!] (restricted)
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  20. Gallant, A. Ronald & Hansen, Lars Peter & Tauchen, George, 1990. "Using conditional moments of asset payoffs to infer the volatility of intertemporal marginal rates of substitution," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 141-179. [Downloadable!] (restricted)
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